1,720,977 research outputs found
A model based method for estimating dimensions and three-dimensional reconstruction of coronary arterial trees from biplane angiograms
No full textDue to relatively large inter- and intra-observer variability of visual interpretation, computer-aided quantitative analysis of coronary arterial dimensions has been a prominent area of research. Luminal configurations of the stenotic coronary arteries at autopsy reveal that the cross-sections of coronary arteries are usually elliptic or circular. The coronary arteries may be represented and visualized efficiently by a generalized cylinder (GC) model with elliptical cross-sections. By using this model and utilizing quadratic expression of an ellipse, the intensity distribution of an ellipse in any image plane, which is perpendicular to the plane of the arterial cross-section, is computed. A nonlinear parametric model for observed intensity distribution of an arterial cross-section is applied to estimate not only cross-sectional areas but also parameters of the ellipse which are essential in three-dimensional (3-D) reconstruction of an arterial segment. This model takes into account background intensity, noise and blurring. Performance of this model has been tested on computer-generated and actual data for various background types and noise values and compared to those of other methods for estimating arterial dimensions. The computed cross-sectional areas from our model for computer-generated as well as actual data demonstrate much less variability than those reported in recent literature. Furthermore, 3-D reconstruction of arterial segments using an elliptical model from computer-generated and actual biplane angiogram data has shown excellent results. Three-dimensional visualization of arterial trees should provide better information for diagnostic decision and management of cardiac patients
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
COMPARISON OF DIFFERENT CLASIFICATION ALGORITHMS USING EASILY CALCULATED FEATURES
No full textTelemedicine has started to be beneficial to patients in remote regions. It is very important to monitor the ECG signals of these patients with heart disorders. Developments in information technology have started to provide important contribution to the clinical decision support systems for early detection and diagnosis. This study aimed to be part of clinical decision support systems and used easily calculated features for detection of ECG arrhythmia. Different classification methods are compared using these features. The performance of the method is tested on data used obtained from the PhysioNet database
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Detecting Cardiac Arrhythmia by Using Time Differences of Double Wavelength PPG Peaks
No full text26th IEEE Signal Processing and Communications Applications Conference (SIU) -- MAY 02-05, 2018 -- Izmir, TURKEYNowadays, photopletismogram (PPG) signals are used in respiration and blood pressure measurement, monitoring of the sleep pattern and also detecting of mental disorders, mainly blood oxygen saturation and heartrate measurement. The reason of the use of PPG signals instead of signals such as electroencephalogram (EEG) or electrocardiogram (ECG) is easy to obtain and real-time monitoring of these data, as well as being easily used by people in daily life and easily integrated into wearable technologies. In this study, detecting of cardiac arrhythmia was made successfully by using double wavelength PPG signals instead of ECG signalsIEEE, Huawei, Aselsan, NETAS, IEEE Turkey Sect, IEEE Signal Proc Soc, IEEE Commun Soc, ViSRATEK, Adresgezgini, Rohde & Schwarz, Integrated Syst & Syst Design, Atilim Univ, Havelsan, Izmir Katip Celebi UnivWOS:0005114485006992-s2.0-8505080793
Investigation of the most appropriate mother wavelet for characterizing imaginary EEG signals used in BCI systems
No full textFeature extraction is a very challenging task, since choosing discriminative features directly affects the recognition rate of the brain computer interface (BCI) system. The objective of this paper is to investigate the effect of mother wavelets (MWs) on classification results. To this end, features were extracted from 3 different datasets using 12 MWs, and then the signals were classified using 3 classification algorithms, including k-nearest neighbor, support vector machine, and linear discriminant analysis. The experiments proved that Daubechies and Shannon were the most suitable wavelet families for extracting more discriminative features from imaginary EEG/ECoG signals
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